Zaihe Cheng1, Yuwen Tao2, Xiaoqing Gu3, Yizhang Jiang2, Pengjiang Qian2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1613-1633, 2023, DOI:10.32604/cmes.2023.027708
Abstract Through semi-supervised learning and knowledge inheritance, a novel Takagi-Sugeno-Kang (TSK) fuzzy system
framework is proposed for epilepsy data classification in this study. The new method is based on the maximum
mean discrepancy (MMD) method and TSK fuzzy system, as a basic model for the classification of epilepsy data.
First, for medical data, the interpretability of TSK fuzzy systems can ensure that the prediction results are traceable
and safe. Second, in view of the deviation in the data distribution between the real source domain and the target
domain, MMD is used to measure the distance between dierent data distributions. The objective… More >
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